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AI-generated content floods web, threatening training data quality

By PulseAugur Editorial · [1 sources] ·

The proliferation of AI-generated content on the open web by mid-2023 has raised concerns about the quality of training data. This trend poses a risk of "model collapse," where AI models trained on their own outputs become less effective. Consequently, there is a growing need for verifiable data provenance to ensure reliable training signals. AI

IMPACT The increasing volume of AI-generated content may degrade the quality of future AI training data, potentially leading to diminished model performance.

RANK_REASON The item discusses a trend and its implications for AI development, offering an opinion on data quality and provenance.

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI-generated content floods web, threatening training data quality

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The item discusses a trend and its implications for AI development, offering an opinion on data quality and provenance.
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138 days old
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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    2023 was the year everyone rushed to scrape everything for training data. Problem is, by mid-2023, a huge chunk of the open web was already AI-generated content

    2023 was the year everyone rushed to scrape everything for training data. Problem is, by mid-2023, a huge chunk of the open web was already AI-generated content. Training on your own outputs creates model collapse. I'm now far more skeptical of any dataset I can't verify the prov…

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